Data-driven insights on the dissemination of antibiotic resistance genes
Doctoral thesis, 2025
antibiotic resistance
phylogenetic analysis
hidden Markov model
microbiome
random forest
horizontal gene transfer
Author
David Lund
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
Extensive screening reveals previously undiscovered aminoglycoside resistance genes in human pathogens
Communications Biology,;Vol. 6(2023)
Journal article
Latent antibiotic resistance genes are abundant, diverse, and mobile in human, animal, and environmental microbiomes
Microbiome,;Vol. 11(2023)p. 44-
Journal article
Lund, D., Johnning, A., Holmström, M., Varghaei, L., Inda-Díaz, J. S., Bengtsson-Palme, J., Kristiansson, E. Community-promoted antibiotic resistance genes show increased dissemination among pathogens.
Parras-Moltó, M., Lund, D., Ebmeyer, S., Larsson, D. G. J., Johnning, A., Kristiansson, E. The transfer of antibiotic resistance genes between evolutionarily distant bacteria.
Genetic compatibility and ecological connectivity drive the dissemination of antibiotic resistance genes
Nature Communications,;Vol. 16(2025)
Journal article
Lund, D., Axillus, S., Larsson, D. G. J., Johnning, A., Kristiansson, E. Can we predict the spread of emerging antibiotic resistance genes?
This thesis applies computational methods to analyze the presence and spread of resistance genes in different environments. Our results reveal a vast number of previously unknown resistance genes in different environments. We also show that the human gut and wastewater environments are connected to the spread of antibiotic resistance genes, and that this process is influenced by the genetic similarity between bacteria. Finally, we show that machine learning can potentially be used to anticipate the spread of new resistance genes. Together, our results provide new knowledge that can inform strategies to combat the spread of antibiotic resistance.
The diversity and mobility of novel antibiotic resistance genes
Swedish Research Council (VR) (2019-03482), 2020-01-01 -- 2023-12-31.
Subject Categories (SSIF 2025)
Bioinformatics and Computational Biology
ISBN
978-91-8103-222-2
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5680
Publisher
Chalmers
Pascal, Chalmers tvärgata 3, Göteborg
Opponent: Professor Sofia Kirke Forslund-Startceva, Max Delbrük Center, Berlin